NATIONAL RESILIENCE THROUGH AI-DRIVEN DATA ANALYTICS AND CYBERSECURITY FOR REAL-TIME CRISIS RESPONSE AND INFRASTRUCTURE PROTECTION

Authors

  • Abdul Awal Mintoo MBA, University of Dhaka, Bangladesh Author
  • Abu Saleh Muhammad Saimon School of Computer and Information Sciences, Washington University of Science and Technology, USA Author
  • Mohammed Majid Bakhsh BBA, North South University, Dhaka, Bangladesh Author
  • Marjina Akter Master of Business Administration in Accounting and Information Systems, Noakhali Science and Technology University, Bangladesh Author

DOI:

https://doi.org/10.63125/sdz8km60

Keywords:

National Resilience, AI-Driven Data Analytics, Cybersecurity, Crisis Response, Critical Infrastructure Protection

Abstract

This study investigates the integration of artificial intelligence (AI) and cybersecurity frameworks in enhancing national resilience through real-time crisis response and critical infrastructure protection. Employing a qualitative case study approach, the research examines twelve carefully selected national and sectoral implementations across diverse contexts, including public health emergencies, smart grid monitoring, intelligent transportation systems, water management, and cyber-physical infrastructure defense. The study reveals that AI-driven data analytics significantly improve early warning capabilities, situational awareness, and decision-making speed in high-risk scenarios. It also demonstrates that the adoption of AI-enhanced cybersecurity tools—such as anomaly detection, behavioral analytics, and autonomous incident response—plays a crucial role in securing digital infrastructure against evolving cyber threats. Furthermore, the application of simulation models and digital twins was found to support real-time modeling, predictive planning, and operational testing, thereby strengthening the adaptability of critical systems. Multi-agent decision support systems and explainable AI interfaces facilitated better interagency coordination and user trust, while zero-trust architectures enabled granular control over access and threat containment. Despite these advancements, the study identified notable gaps in methodological integration, sectoral coverage (particularly in education and water sanitation), and inclusive system design. The findings emphasize the importance of interdisciplinary collaboration and governance alignment in developing comprehensive AI and cybersecurity strategies for national resilience. By synthesizing empirical evidence from twelve cross-sectoral case studies, this research contributes actionable insights into the design and implementation of intelligent, secure, and adaptive infrastructure systems in an era of complex and interconnected global threats.

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Published

2022-03-01

How to Cite

Abdul Awal Mintoo, Abu Saleh Muhammad Saimon, Mohammed Majid Bakhsh, & Marjina Akter. (2022). NATIONAL RESILIENCE THROUGH AI-DRIVEN DATA ANALYTICS AND CYBERSECURITY FOR REAL-TIME CRISIS RESPONSE AND INFRASTRUCTURE PROTECTION. American Journal of Scholarly Research and Innovation, 1(01), 137-169. https://doi.org/10.63125/sdz8km60